Post Doctoral Fellow - Computational Medicine

About the role

Department: Electrical Engineering

Position Summary: The Spatial Artificial Intelligence Lab at the University of Houston is seeking a highly motivated Postdoctoral Fellow to join our newly established and growing research team. Our research develops AI and machine-learning methods to advance biological and clinical discovery, with particular interests in single-cell and spatial biology, biomedical imaging, and cancer research. The successful candidate will have opportunities to lead interdisciplinary research projects, develop independent research directions, collaborate with biomedical and clinical investigators, and contribute to high-impact publications and grant proposals. More information about the laboratory and current research can be found at https://zheng-lab.org/.

Research Areas: Our research aims to develop and deploy novel computational frameworks that integrate digital pathology, spatial and single-cell omics, genomics, and clinical data to model tissue architectures and signaling environments in health and disease, with the overarching goal of uncovering mechanisms underlying treatment resistance and advancing precision medicine.

Responsibilities

• Develop and apply bioinformatics, machine learning and deep-learning methods to extract biologically and clinically relevant insights from multimodal biomedical datasets.
• Design, develop and maintain computational pipelines to analyze large-scale biomedical data including digital pathology images, spatial transcriptomics, single-cell data, genomics, and clinical data.
• Conduct research related to tissue characterization, feature extraction, tumor immune microenvironments and precision oncology.
• Design and execute computational experiments and perform rigorous statistical analyses.
• Prepare manuscripts for publication in peer-reviewed journals and present findings at scientific conferences.
• Collaborate with investigators across computational science, biology, pathology, and medicine.
• Contribute to the development of research proposals and grant applications.
• Assist with mentoring graduate and undergraduate researchers.
• Participate in laboratory meetings and contribute to the development of a collaborative and supportive research environment.

Requirements

• A Ph.D. or equivalent doctoral degree in Bioinformatics, Computational Biology, Computer Science, Data Science, Biomedical Engineering, or a closely related discipline by the anticipated start date.
• Strong quantitative and computational research training.
• Proficiency in programming languages commonly used for scientific computing, such as Python and/or R.
• Experience conducting independent research and communicating research findings.
• Strong written and oral communication skills.
• The ability to work effectively both independently and as part of an interdisciplinary research team.

Qualifications

• Experience in one or more of the following areas is preferred:
  • Machine learning or deep learning.
  • Foundation models, representation learning, or multimodal learning.
  • Computational pathology or medical image analysis.
  • Single-cell or spatial transcriptomics.
  • Genomics or computational biology.
  • Tumor immunology or cancer research.
  • Development of reproducible computational pipelines or research software.

Benefits

• Access to state-of-the-art computational resources and high-performance computing infrastructure.
• Opportunities for working with an interdisciplinary team in a highly collaborative environment.
• Close collaboration with researchers across pathology, clinical medicine, biology and engineers.
• Structured mentoring and accessible support for research, manuscript preparation, and presentations.
• Support for fellowship and career development award applications and preparation for future academic, research, or industry careers.